Theory of constraints

this presentation discusses the Theory of constraints as its aims and how to achieve them.

1. Prepared By Mohamed Ahmed Sadek Ayman Hisham Mahmoud Mahmoud Ahmed El-Sayed Submitted to Dr. Ehab Abdelaaty Abdelhafiz Theory of Constraints (TOC) B.N 13 28 Group #7

2. Presentation Contents Problem Statement Goldratt’s Rules of Production Scheduling Goldratt’s Theory of Constraints (TOC) Performance Measurements Unbalanced Capacity Dependent Events and Statistical Fluctuations Definitions The Basic Building Blocks of Manufacturing Derived by Grouping Process Flows Product Flow through Bottlenecks and Non-bottlenecks Time Components 1

3. Finding Bottleneck Saving Time Avoid Changing a Non-bottleneck into a Bottleneck Drum, Buffer and Rope Network Flow with One Bottleneck Batch Size How to Determine Process Batch and Transfer Batch Sizes How to Treat Inventory Dollar Days How Much to Produce? (EXAMPLE) Conclusion Presentation Contents 2

4. The Story describes the hike out to the campsite. They are way behind schedule and the line of scouts is spread out over a long distance. The fastest kids are up front, and poor Herbie, the slowest kid, lags way behind at the end of the line. The goal is to get all the kids to the campsite as quickly as possible. The hike leader stops the hike and tells everyone in the troop to hold hands with the person before and after him, and to not let go. He then takes Herbie, who is in the back, and leads him to the front of the line. He keeps walking with Herbie turning the troop around so that Herbie, the slowest, is now leading and Andy, the fastest, is now at the end. Now, the hike speed is limited to the slowest person speed (The Bottleneck) , if they want to go faster, they need to figure out a way Herbie can go faster. A Story to Demonstrate the Effect of Bottleneck and the Impact of Changing its Constraints. Problem Statement 3

5. T hey find that he is carrying a backpack much heavier than the others. So, they decide to take some of the load off Herbie by carrying some of his stuff. Now Herbie can really move, since most of the weight in his pack is removed (Changing Constraints). The troop is now moving at twice the speed it was before and they are still staying together. 4 Problem Statement

6. 1. Do not balance capacity—balance the flow. 2. The level of utilization of a non-bottleneck resource is determined not by its own potential but by some other constraint in the system. 3. Utilization and activation of a resource are not the same. 4. An hour lost at a bottleneck is an hour lost for the entire system. 5. An hour saved at a non-bottleneck is a mirage. 6. Bottlenecks govern both throughput and inventory in the system. 7. The transfer batch may not, and many times should not, be equal to the process batch. 8. A process batch should be variable both along its route and in time. 9. Priorities can be set only by examining the system’s constraints. Lead time is a derivative of the schedule. Goldratt’s Rules of Production Scheduling 5

7. Goldratt’s Theory of Constraints (TOC) 1. Identify the system constraints. (No improvement is possible unless the constraint or weakest link is found.) 2. Decide how to exploit the system constraints. (Make the constraints as effective as possible.) 3. Subordinate everything else to that decision. (Align every other part of the system to support the constraints even if this reduces the efficiency of non-constraint resources.) 4. Elevate the system constraints. (If output is still inadequate, acquire more of this resource so it no longer is a constraint.) 5. If, in the previous steps, the constraints have been broken, go back to Step 1, but do not let inertia become the system constraint. (After this constraint problem is solved, go back to the beginning and start over. This is a continuous process of improvement: identifying constraints, breaking them, and then identifying the new ones that result.) 6

8. Performance Measurements Financial Measurements We have three measures of the firm’s ability to make money: 1. Net profit—an absolute measurement in dollars. 2. Return on investment—a relative measure based on investment. 3. Cash flow—a survival measurement. 7

9. Operational Measurements Financial measurements work well at the higher level, but they cannot be used at the operational level. We need another set of measurements that will give us guidance: 1. Throughput —the rate at which money is generated by the system through sales. 2. Inventory —all the money that the system has invested in purchasing things it intends to sell. 3. Operating expenses —all the money that the system spends to turn inventory into throughput. Performance Measurements (Cont .) 8

10. Productivity Typically, productivity is measured in terms of output per labor hour. However, this measurement does not ensure that the firm will make money (for example, when extra output is not sold but accumulates as inventory). To test whether productivity has increased, we should ask these questions: Has the action taken increased throughput? Has it decreased inventory? Has it decreased operational expense? This leads us to a new definition: PRODUCTIVITY IS ALL THE ACTIONS THAT BRING A COMPANY CLOSER TO ITS GOALS. Performance Measurements (Cont .) 9

11. Historically (and still typically in most firms), manufacturers have tried to balance capacity across a sequence of processes in an attempt to match capacity with market demand. However, this is the wrong thing to do—unbalanced capacity is better. Thus, making all capacities the same is viewed as a bad decision. Such a balance would be possible only if the output times of all stations were constant or had a very narrow distribution. A normal variation in output times causes downstream stations to have idle time when upstream stations take longer to process. Conversely, when upstream stations process in a shorter time, inventory builds up between the stations. The effect of the statistical variation is cumulative. The only way that this variation can be smoothed is by increasing work-in-process to absorb the variation (a bad choice because we should be trying to reduce work-in-process) or increasing capacities downstream to be able to make up for the longer upstream times. Unbalanced Capacity 10

12. Dependent Events and Statistical Fluctuations Here the flow is from Process A (on the left) to Process B (on the right). Process A has a mean of 10 hours and a standard deviation of 2 hours; Process B has a constant 10-hour processing time. 11

13. This is similar to Previous Example. However, the processing sequence has been reversed, as well as the order of the Process A times. 12 Dependent Events and Statistical Fluctuations (Cont.)

14. B ottleneck: is defined as any resource whose capacity is less than the demand placed upon it. A bottleneck is a constraint within the system that limits throughput. It is that point in the manufacturing process where flow thins to a narrow stream. A bottleneck may be a machine, scarce or highly skilled labor, or a specialized tool. N on-bottleneck: is any resource whose capacity is greater than the demand placed on it. A non-bottleneck, therefore, should not be working constantly because it can produce more than is needed. A non-bottleneck contains idle time. C apacity-constrained resource (CCR): is one whose utilization is close to capacity and could be a bottleneck if it is not scheduled carefully. For example, a CCR may be receiving work in a job-shop environment from several sources. If these sources schedule their flow in a way that causes occasional idle time for the CCR in excess of its unused capacity time, the CCR becomes a bottleneck when the surge of work arrives at a later time. This can happen if batch sizes are changed or if one of the upstream operations is not working for some reason and does not feed enough work to the CCR. Definitions 13

15. The Basic Building Blocks of Manufacturing Derived by Grouping Process Flows 14

16. Product Flow through Bottlenecks and Non - bottlenecks 15

17. Situation A shows a bottleneck feeding a non - bottleneck. Product flows from Work center X to Work center Y. X is the bottleneck because it has a capacity of 200 units (200 hours/ 1 hour per unit) and Y has a capacity of 267 units (200 hours/45 minutes per unit). Because Y has to wait for X, and Y has a higher capacity than X, no extra product accumulates in the system. It all flows through to the market. Situation B is the reverse of A, with Y feeding X. This is a non - bottleneck feeding a bottleneck. Because Y has a capacity of 267 units and X has a capacity of only 200 units, we should produce only 200 units of Y (75 percent of capacity) or else work-in-process will accumulate in front of X. Situation C shows that the products produced by X and Y are assembled and then sold to the market. Because one unit from X and one unit from Y form an assembly, X is the bottleneck with 200 units of capacity and, therefore, Y should not work more than 75 percent or else extra parts will accumulate. Situation D , equal quantities of product from X and Y are demanded by the market. In this case, we can call these products “finished goods” because they face independent demands. Here, Y has access to material independent of X and, with a higher capacity than needed to satisfy the market (in essence, the market is the bottleneck), it can produce more product than the market will take. However, this would create an inventory of unneeded finished goods. 16 Product Flow through Bottlenecks and Non - bottlenecks (Cont .)

18. The following kinds of time make up production cycle time: 1. Setup time—the time that a part spends waiting for a resource to be set up to work on this same part. 2. Processing time—the time that the part is being processed. 3. Queue time—the time that a part waits for a resource while the resource is busy with something else. 4. Wait time—the time that a part waits not for a resource but for another part so that they can be assembled together. 5. Idle time—the unused time; that is, the cycle time minus the sum of the setup time, processing time, queue time, and wait time. Time Components 17

19. Finding Bottleneck 18 The first way is to use your knowledge of a particular plant to identify the bottleneck. 1. Use your experience about the plant. 2. Talk through the shop floor workers and supervisors.

20. Finding Bottleneck (Cont.) 19 The Second way is to run a capacity resource profile Resource capacity profile = Loads/resource Capacity Getting the resources capacity profile in percentage, we first assume that our data are reasonably accurate, although not necessarily perfect. We disregards all lower percentages as this means this resource is a none bottleneck. We should observe high inventory laying in front of the highest percentage resource (bottleneck), Overloaded resource.

21. Recall that a bottleneck is a resource whose capacity is less than the demand placed on it. Because we focus on bottlenecks as restricting throughput ( defined as sales), a bottleneck’s capacity is less than the market demand. There are a number of ways we can save time on a bottleneck: B etter tooling. Higher-quality labor. L arger batch sizes. R eduction in setup times, and so on. AN HOUR SAVED AT THE BOTTLENECK ADDS AN EXTRA HOUR TO THE ENTIRE PRODUCTION SYSTEM. How about time saved on a non-bottleneck resource? AN HOUR SAVED AT A NONBOTTLENECK IS A MIRAGE AND ONLY ADDS AN HOUR TO ITS IDLE TIME. Because a non-bottleneck has more capacity than the system needs for its current throughput, It already contains idle time. Implementing any measures to save more time does not increase throughput but only serves to increase its idle time. Saving Time 20

22. When non-bottleneck resources are scheduled with larger batch sizes, this action could create a bottleneck that we certainly would want to avoid. W here Y1, Y2, and Y3 are non-bottleneck resources. Y1 currently produces Part A, which is routed to Y3, and Part B, which is routed to Y2. To produce Part A, Y1 has a 200-minute setup time and a processing time of 1 minute per part. Part A is currently produced in batches of 500 units. To produce Part B, Y1 has a setup time of 150 minutes and 2 minutes’ processing time per part. Part B is currently produced in batches of 200 units. With this sequence, Y2 is utilized 70 percent of the time and Y3 is utilized 80 percent of the time. Because setup time is 200 minutes for Y1 on Part A, both worker and supervisor mistakenly believe that more production can be gained if fewer setups are made. Let’s assume that the batch size is increased to 1,500 units and see what happens. The illusion is that we have saved 400 minutes of setup. (Instead of three setups taking 600 minutes to produce three batches of 500 units each, there is just one setup with a 1,500-unit batch.) Avoid Changing a Non-bottleneck into a Bottleneck 21

23. The problem is that the 400 minutes saved served no purpose, but this delay did interfere with the production of Part B because Y1 produces Part B for Y2. The sequence before any changes were made was Part A (700 minutes), Part B (550 minutes), Part A (700 minutes), Part B (550 minutes), and so on. Now, however, when the Part A batch is increased to 1,500 units (1,700 minutes), Y2 and Y3 could well be starved for work and have to wait more time than they have available (30 percent idle time for Y2 and 20 percent for Y3). The new sequence would be Part A (1,700 minutes), Part B (1,350 minutes), and so on. Such an extended wait for Y2 and Y3 could be disruptive. Y2 and Y3 could become temporary bottlenecks and lose throughput for the system. Avoid Changing a Non-bottleneck into a Bottleneck (Cont.) 22

24. Drum, Buffer and Rope Linear Flow of Product with a Bottleneck There are two things we must do with this bottleneck: 1. Keep a buffer inventory in front of it to make sure it always has something to work on. Because it is a bottleneck, its output determines the throughput of the system. 2. Communicate back upstream to A what D has produced so that A provides only that amount. This keeps inventory from building up. This communication is called the rope. It can be formal (such as a schedule) or informal (such as daily discussion). Figure shows a simple linear flow A through G. Suppose that Resource D, which is a machine center, is a bottleneck. This means the capacities are greater both upstream and downstream from it. If this sequence is not controlled, we would expect to see a large amount of inventory in front of Work center D and very little anywhere else. There would be little finished goods inventory because (by the definition of the term bottleneck) all the product produced would be taken by the market. 23

25. If the drum is not a bottleneck but a CCR (and thus it can have a small amount of idle time), we might want to create two buffer inventories: one in front of the CCR and the second at the end as finished goods. (See Figure.) The finished-goods inventory protects the market, and the time buffer in front of the CCR protects throughput. For this CCR case, the market cannot take all that we can produce, so we want to ensure that finished goods are available when the market does decide to purchase. Linear Flow of Product with a Capacity-Constrained Resource We need two ropes in this case: 1. a rope communicating from finished-goods inventory back to the drum to increase or decrease output. 2. a rope from the drum back to the material release point, specifying how much material is needed. Drum, Buffer and Rope (Cont.) 24

26. The figure shows a more detailed network flow showing one bottleneck. Inventory is provided not only in front of that bottleneck but also after the non-bottleneck sequence of processes that feed the subassembly. This ensures that the flow of product is not slowed down by having to wait after it leaves the bottleneck. Network Flow with One Bottleneck 25

27. The advantage of using transfer batches that are smaller than the process batch quantity is that the total production time is shorter, so the amount of work-in-process is smaller. This Figure shows a situation where the total production lead time was reduced from 2,100 to 1,310 minutes by (1) using a transfer batch size of 100 rather than 1,000 and (2) reducing the process batch sizes of Operation 2. Effect of Changing the Process Batch Sizes on Production Lead Time Batch Size 26

28. When trying to control the flow at CCRs and bottlenecks, there are four possible situations: A bottleneck (no idle time) with no setup time required when changing from one product to another. 2. A bottleneck with setup time required to change from one product to another. 3. A capacity-constrained resource with a small amount of idle time, with no setup time required to change from one product to another. 4. A CCR with setup time required when changing from one product to another. How to Determine Process Batch and Transfer Batch Sizes 27

29. From a constraint management perspective, inventory is a loan given to the manufacturing unit. The value of the loan is based only on the purchased items that are part of the inventory. As we stated earlier, inventory is treated in this chapter as material cost only, without any accounting type value added from production. If inventory is carried as a loan to manufacturing, we need a way to measure how long the loan is carried. One measurement is dollar days. How to Treat Inventory 28

30. A useful performance measurement is the concept of dollar days , a measurement of the value of inventory and the time it stays within an area. To use this measure, we could simply multiply the total value of inventory by the number of days inventory spends within a department. Suppose Department X carries an average inventory of $40,000, and, on average, the inventory stays within the department five days. In dollar days, Department X is charged with $40,000 times five days, or $200,000 dollar days of inventory. At this point, we cannot say the $200,000 is high or low, but it does show where the inventory is located. Management can then see where it should focus attention and determine acceptable levels. Techniques can be instituted to try to reduce the number of dollar days while being careful that such a measure does not become a local objective (that is, minimizing dollar days) and hurt the global objectives (such as increasing ROI, cash flow, and net profit). Dollar Days 29

31. Dollar days could be beneficial in a variety of ways. Consider the current practice of using efficiencies or equipment utilization as a performance measurement. To get high utilization, large amounts of inventory are held to keep everything working. However, high inventories would result in a high number of dollar days, which would discourage high levels of work-in-process. Dollar day measurements also could be used in other areas: Marketing—to discourage holding large amounts of finished-goods inventory. The net result would be to encourage the sales of finished products. Purchasing—to discourage placing large purchase orders that on the surface appear to take advantage of quantity discounts. This would encourage just-in-time purchasing. Manufacturing—to discourage large work-in-process and producing earlier than needed. This would promote rapid flow of material within the plant. Project management—to quantify a project’s limited resource investments as a function of time. This promotes the proper allocation of resources to competing projects. Dollar Days (Cont.) 30

32. How Much to Produce? (EXAMPLE) 31

33. SOLUTION As in the previous example, there are three answers to this question, depending on each of the following objectives: 1. Maximize revenue for sales personnel, who are paid on commission. 2. Maximize per unit gross profit. 3. Maximize the utilization of the bottleneck resource (leading to maximum gross profit). How Much to Produce? (EXAMPLE) 32

34. How Much to Produce? (EXAMPLE) 33

35. How Much to Produce? (EXAMPLE) 34

36. How Much to Produce? (EXAMPLE) 35

37. How Much to Produce? (EXAMPLE) 36

38. Eli Goldratt developed his Theory of Constraints as an alternative way to think about improving processes. His ideas have stimulated thought by practitioners due to their applicability to many areas, including production, distribution, and project management. His underlying philosophy is that it is essential to concentrate on system limitations imposed by capacity constrained resources, and for a firm to make money, it must systematically remove these limitations.  He argues that, to do this, the firm must simultaneously increase throughput, reduce inventory, and reduce operating expenses.  He argues that improving labor productivity will not necessarily make money for the firm, and will only do so when it increases throughput, reduces inventory, or reduces operating expenses. Goldratt argues that trying to maintain perfectly balanced capacity leads to many problems because this makes every resource dependent on every other. Since statistical fluctuations are inherent in any process, perfect balance leads to disruptions. He argues that not capacity, but flow through the process, should be balanced. Conclusion 37

39. Thanks